create_image ¶

def create_image(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    description: Optional[
        "capo_sagemaker.types.image_description.ImageDescription"
    ] = None,
    display_name: Optional[
        "capo_sagemaker.types.image_display_name.ImageDisplayName"
    ] = None,
    image_name: Optional["capo_sagemaker.types.image_name.ImageName"] = None,
    role_arn: Optional["capo_sagemaker.types.role_arn.RoleArn"] = None,
    tags: Optional["capo_sagemaker.types.tag_list.TagList"] = None,
) -> "capo_sagemaker.types.create_image_response.CreateImageResponse":
    """<p>Creates a custom SageMaker AI image. A SageMaker AI image is a set of image versions. Each image version represents a container image stored in Amazon ECR. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/studio-byoi.html">Bring your own SageMaker AI image</a>.</p>

    Args:
        description: <p>The description of the image.</p>
        display_name: <p>The display name of the image. If not provided, <code>ImageName</code> is displayed.</p>
        image_name: <p>The name of the image. Must be unique to your account.</p>
        role_arn: <p>The ARN of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.</p>
        tags: <p>A list of tags to apply to the image.</p>

    Raises:
        capo_sagemaker.errors.resource_in_use.ResourceInUse: <p>Resource being accessed is in use.</p>
        capo_sagemaker.errors.resource_limit_exceeded.ResourceLimitExceeded: <p> You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. </p>
        capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_sagemaker.types.create_image_request.CreateImageRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.create_image_response.CreateImageResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.create_image

        output, http_response = (
            capo_sagemaker._operations.sage_maker.create_image.create_image(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CreateImage")
    )
    input_: capo_sagemaker.types.create_image_request.CreateImageRequest = {}
    if description is not None:
        input_["description"] = description
    if display_name is not None:
        input_["display_name"] = display_name
    if image_name is not None:
        input_["image_name"] = image_name
    if role_arn is not None:
        input_["role_arn"] = role_arn
    if tags is not None:
        input_["tags"] = tags

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output